%0 Journal Article %T Detecting tag spam in social tagging systems with kernel K-meansclustering and semi-definite programming SVM
用核K-means聚类和半定规划SVM实现垃圾标签检测 %A QIN Hu %A DING Li-duo %A FU Li-jin %A QIN Xi %A
覃 华 %A 丁立朵 %A 符丽锦 %A 覃 希 %J 计算机应用研究 %D 2013 %I %X This paper presented a method. It used kernel K-means clustering algorithm to extract the character vector set from the samples and got the optimal combinatorial coefficients of different functions to construct semi-definite programming SVM with stronger nonlinear mapping ability. Experimental results on UCI datasets show that compared with double-layer reduction method, the new method gives higher accuracy and speeds up obviously. %K tag spam detection %K SVM %K combination of multiple kernel functions %K semi-definite programming
垃圾标签识别 %K 支持向量机 %K 多核函数组合 %K 半定规划 %U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=DD8ECC43358E540D2FD7BE65B592BDA5&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=E158A972A605785F&sid=4206C58D935377EA&eid=7CCBDF94263DBB99&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=20